Triple
T935302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ten Plagues of Egypt |
E20181
|
entity |
| Predicate | plague |
P21762
|
FINISHED |
| Object | Water turned to blood |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Water turned to blood | Statement: [Ten Plagues of Egypt, plague, Water turned to blood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plague Context triple: [Ten Plagues of Egypt, plague, Water turned to blood]
-
A.
placeOfDeath
Indicates the location where an entity (typically a person or animal) died.
-
B.
death
Indicates the event or state in which an entity ceases to live or exist, marking the end of its biological or functional processes.
-
C.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
D.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or condition.
-
E.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b363ea5c819098ec1d87f785bad4 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.